Local Search Algorithms
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Questions and Answers

What type of search trees are used in planning under uncertainty?

  • Decision trees
  • OR-AND search trees
  • AND-OR search trees (correct)
  • OR search trees
  • Which of the following is NOT a type of local search algorithm?

  • Genetic algorithms
  • Hill-climbing search
  • Simulated annealing
  • Breadth-first search (correct)
  • In sensorless problem solving, what is the agent's situation?

  • The agent has partial observations
  • The agent has uncertain knowledge
  • The agent has no observation (correct)
  • The agent has complete knowledge of the environment
  • What is the main difference between an AND node and an OR node in an AND-OR search tree?

    <p>An AND node represents a conjunction, an OR node represents a disjunction</p> Signup and view all the answers

    Which of the following is an example of a problem formulation?

    <p>The erratic vacuum world</p> Signup and view all the answers

    What is the main difference between a local search algorithm and a systematic search algorithm?

    <p>Systematic search algorithms are complete, local search algorithms are not</p> Signup and view all the answers

    Study Notes

    Local Search Algorithms

    • Primarily designed for pure optimization problems, aiming to identify the best possible state based on an objective function.

    State-Space Landscape

    • The concept of state-space landscape is critical for understanding local search methodologies.
    • It represents the different states available in an optimization problem and their relationships to each other.
    • A local beam search operates by exploring multiple states in parallel and shares useful information among these threads to enhance search efficiency.
    • May suffer from limited diversity when exploring k states, potentially causing the search to focus too narrowly in a confined area of the state space.
    • This concentration can lead to suboptimal solutions as it might overlook broader areas that could contain better states.

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    Description

    Learn about local search algorithms and how they are used to solve pure optimization problems. Understand the concept of state-space landscape and its relation to local search.

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